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Record W2074112103 · doi:10.1016/j.pain.2004.03.027

Effects of exposure on perception of pain expression

2004· article· en· W2074112103 on OpenAlexaff
Kenneth M. Prkachin, Heather Mass, Susan R. Mercer

Bibliographic record

VenuePain · 2004
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsFacial expressionStimulus (psychology)PerceptionPain perceptionAudiologyPsychologyExpression (computer science)MedicinePhysical therapyCognitive psychologyCommunicationNeuroscience

Abstract

fetched live from OpenAlex

The present study evaluated the effects of exposure to facial expression of pain, on observers' perceptions of pain expression. Thirty-one male and 49 female observers judged 1-s video excerpts in a signal detection paradigm. The excerpts showed facial expressions of shoulder-pain patients displaying no pain or moderate pain. Participants were randomly allocated to one of four groups, which varied in the number of prior exposures of a 1 s display of strong pain. On each test trial, participants indicated whether the test stimulus showed no pain or pain. Data were analyzed using signal detection theory methods. There was a linear relationship between the density of exposure to strong pain and observers' response criteria: greater exposure was associated with more conservative decisions. On average, participants showed very high levels of sensitivity to pain expression, with women significantly outperforming men. Results are discussed in terms of their implications for pain judgments of health care professionals, adaptation-level theory, and the psychophysical method of selective adaptation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.273
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations74
Published2004
Admission routes1
Has abstractyes

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